Clinical decision support systems utilizing Clinical Decision Support (CDS) tools have become a leading response to the growing demand for the promotion of standards-based care delivery. CDS tools are important components of clinical Information Technology (IT) systems and may directly improve patient care outcomes and the performance of healthcare organizations. The development and use of CDS tools at the point of care offers medical professionals the ability to analyze and work with patient data in real-time while making critical decisions.
With respect to the cost of treatment and complexity of management of patients in a medical facility, in particular heart failure (HF) patients because of the difficult HF etiology and many co-morbidities like sleep apnea, hypertension, diabetes, chronic obstructive pulmonary disease (COPD), and renal dysfunction, the demand is huge and growing because of an aging population and in part to re-hospitalization of the HF patient after discharge. A large part of this cost, estimated to be at forty-two (42%), is regarded as preventable by proper treatment prior to and after discharge from the hospital.
Nowadays discharge criteria are physician dependent, i.e., they differ per country, hospital, and even physician. The American College of Cardiology/American Heart Association (ACC/AHA) and the European Society of Cardiology (ESC) guidelines do not specify discharge criteria. Only the Heart Failure Society of America (HFSA) guidelines list a number of discharge criteria with Strength of Evidence C (=low) indicative of missing evidence on how effective those discharge criteria are with respect to outcomes. Further, current methods of determining whether HF patients are at a high risk of adverse effects (e.g., HF exacerbation often result in frequent re-admissions and high mortality rates) are used only in clinical research and not in daily practice due to missing tools, bringing the complex risk nomograms into the daily clinicians workflow. The existing methods for medical professionals to prepare the patient for disease management in out-of-hospital settings and propose guideline-based post-discharge therapy can be improved with respect to efficiency and effectiveness. Current methods of providing discharge instructions for HF patients include approximately one hour of manual instruction by the care provider on the last day of the hospital stay which leads to patient information overload and poor post-discharge care results.
In addition, there is currently no method of effectively ensuring continuity of care from the hospital care team who treated the HF patient by sharing the status of the HF patient with other professionals responsible for post-discharge care of the HF patient.